HSAT has unveiled a technological breakthrough in predicting cocoa yields, consistently delivering accuracy levels above 95%.
This progress positions HSAT’s CropGPT as the global benchmark for AI-powered cocoa production forecasting.
Feeding on billions of data points and refreshed twice hourly, the platform merges satellite data, highly localised weather insights, crop survey inputs, disease outbreak signals, and economic factors spanning cocoa hubs including Ivory Coast, Ghana, Ecuador, Nigeria, and Indonesia.
Predictions are validated through independent methods, including on-the-ground verification by HSAT’s global field team of over 2,000 contributors.
HSAT’s cocoa forecasting models are tailored to regional agronomic conditions and adapt in real time. Disease mapping (e.g., CSSV), AI-driven pod counting, and cumulative rainfall analysis are key innovations that allow HSAT to detect yield threats before they impact production – delivering intelligence to traders, insurers, and producers with unmatched lead time and precision.
“Our models aren’t static forecasts, they evolve each week,” said Rob Weston, founder. “We show our accuracy over the past decade, and every model is specific to crop, country, and season. This level of granularity is unique in the market.”
HSAT’s predictions are actively used by major soft commodity traders, food producers, and hedge funds to manage risk and improve strategic planning.
The cocoa insights feed directly into HSAT’s Market Forces system – enabling users to track how rainfall deficits, disease outbreaks, or FX movements impact future yields.
A detailed report on the impact of disease in Ivory Coast and Ghana – two of the world’s largest cocoa producers – is available at https://reports.cropgpt.ai/cocoadisease.
